A survey on modality characteristics, performance evaluation metrics, and security for traditional and wearable biometric systems

Aditya Sundararajan, Arif I. Sarwat, Alexander Pons

Research output: Contribution to journalReview articlepeer-review

41 Scopus citations

Abstract

Biometric research is directed increasingly toward Wearable Biometric Systems (WBS) for user authentication and identification. However, prior to engaging in WBS research, how their operational dynamics and design considerations differ from those of Traditional Biometric Systems (TBS) must be understood. While the current literature is cognizant of those differences, there is no effective work that summarizes the factors where TBS and WBS differ, namely, their modality characteristics, performance, security, and privacy. To bridge the gap, this article accordingly reviews and compares the key characteristics of modalities, contrasts the metrics used to evaluate system performance, and highlights the divergence in critical vulnerabilities, attacks, and defenses for TBS and WBS. It further discusses how these factors affect the design considerations for WBS, the open challenges, and future directions of research in these areas. In doing so, the article provides a big-picture overview of the important avenues of challenges and potential solutions that researchers entering the field should be aware of. Hence, this survey aims to be a starting point for researchers in comprehending the fundamental differences between TBS and WBS before understanding the core challenges associated with WBS and its design.

Original languageEnglish
Article numbera39
JournalACM Computing Surveys
Volume52
Issue number2
DOIs
StatePublished - May 2019
Externally publishedYes

Funding

This work is supported by the National Science Foundation under Grant No. 1553494. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. Authors’ addresses: A. Sundararajan, A. I. Sarwat, and A. Pons, Department of Electrical and Computer Engineering, Florida International University, 10555 West Flagler Street, Miami, FL USA, 33174. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]. © 2019 Association for Computing Machinery. 0360-0300/2019/05-ART39 $15.00 https://doi.org/10.1145/3309550

FundersFunder number
National Science Foundation1553494

    Keywords

    • Attacks
    • Biometrics
    • Metrics
    • Threats
    • Vulnerabilities
    • WBAN
    • Wearables

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